1 to 25 of 182 Permanent Amazon Redshift Jobs in England

processing) Apache Spark Streaming, Kafka or similar (for real-time data streaming) Experience using data tools in at least one cloud service - AWS, Azure or GCP (e.g. S3, EMR, Redshift, Glue, Azure Data Factory, Databricks, BigQuery, Dataflow, Dataproc) Would you like to join us as we work hard, have fun and make history? Apply for this job indicates a More ❯

with data privacy regulations. Technical Competencies The role is a hands-on technical leadership role with advanced experience in at least most of the following technologies Cloud Platforms: AWS (Amazon Web Services): Knowledge of services like S3, EC2, Lambda, RDS, Redshift, EMR, SageMaker, Glue, and Kinesis. Azure: Proficiency in services like Azure Blob Storage, Azure Data Lake, VMs … Formation, Azure Purview. Data Security Tools: AWS Key Management Service (KMS), Azure Key Vault. Data Analytics & BI: Visualization Tools: Tableau, Power BI, Looker, and Grafana. Analytics Services: AWS Athena, Amazon QuickSight, Azure Stream Analytics. Development & Collaboration Tools: Version Control: Git (and platforms like GitHub, GitLab). CI/CD Tools: Jenkins, Travis CI, AWS CodePipeline, Azure DevOps. Other Key More ❯

consultants. Knowledge and Skills: Knowledge • Broad data management technical knowledge so as to be able to work across full data cycle. • Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD • Coding experience in Apache Spark, Iceberg or Python (Pandas) • Experience in change and release management. • Experience in Database Warehouse … procedures. Technical Essentials: • Expertise across data warehouse and ETL/ELT development in AWS preferred with experience in the following: • Strong experience in some of the AWS services like Redshift, Lambda,S3,Step Functions, Batch, Cloud formation, Lake Formation, Code Build, CI/CD, GitHub, IAM, SQS, SNS, Aurora DB • Good experience with DBT, Apache Iceberg, Docker, Microsoft BI More ❯

the team. Drive the design development and implementation of complex data pipelines and ETL/ELT processes using cloud-native technologies (e.g. AWS Glue AWS Lambda AWS S3 AWS Redshift AWS EMR). Develop and maintain data quality checks data validation rules and data lineage documentation. Collaborate with data analysts data scientists business stakeholders and product owners to understand More ❯

processing) Apache Spark Streaming, Kafka or similar (for real-time data streaming) Experience using data tools in at least one cloud service - AWS, Azure or GCP (e.g. S3, EMR, Redshift, Glue, Azure Data Factory, Databricks, BigQuery, Dataflow, Dataproc Would you like to join us as we work hard, have fun and make history? Apply for this job indicates a More ❯

AWS CloudFormation, Terraform). Deep expertise in AWS (EC2, S3, Lambda, API Gateway) or equivalent services in GCP/Azure. Proficiency with SQL and NoSQL databases (e.g., MySQL, PostgreSQL, Redshift, Snowflake, DynamoDB, MongoDB). Strong coding practices and experience implementing robust data quality and monitoring frameworks. Understanding of data security, governance, and compliance. Working experience of data governance and More ❯

Skillset Delivery experience Building solutions in snowflake Insurance experience - advantageous but not necessary MUST HAVE SNOWFLAKE, AWS, SNOWPRO CORE Key Responsibilities: Lead the design and implementation of Snowflake [and Redshift] based data warehousing solutions within an AWS environment Mentoring of team members through code reviews and pair programming Build and support new AWS native cloud data warehouse solutions Develop … experience as a data engineer with a strong focus on Snowflake and AWS services in large-scale enterprise environments Extensive experience in AWS services, e.g. EC2, S3, RDS, DynamoDB, Redshift, Lambda, API Gateway Strong SQL skills for complex data queries and transformations Python programming for data processing and analysis is a plus Strong acumen for application health through performance More ❯

focus on building scalable data solutions. Experience with data pipeline orchestration tools such as Dagster or similar. Familiarity with cloud platforms (e.g. AWS) and their data services (e.g., S3, Redshift, Snowflake). Understanding of data warehousing concepts and experience with modern warehousing solutions. Experience with GitHub Actions (or similar) and implementing CI/CD pipelines for data workflows and More ❯

interested in building data and science solutions to drive strategic direction? Based in Tokyo, the Science and Data Technologies team designs, builds, operates, and scales the data infrastructure powering Amazon's retail business in Japan. Working with a diverse, global team serving customers and partners worldwide, you can make a significant impact while continuously learning and experimenting with cutting … working with large-scale data, excels in highly complex technical environments, and above all, has a passion for data. You will lead the development of data solutions to optimize Amazon's retail operations in Japan, turning business needs into robust data pipelines and architecture. Leveraging your deep experience in data infrastructure and passion for enabling data-driven business impact … with scientists, software engineers and business teams to identify and implement strategic data opportunities. Key job responsibilities Your key responsibilities include: - Create data solutions with AWS services such as Redshift, S3, EMR, Lambda, SageMaker, CloudWatch etc. - Implement robust data solutions and scalable data architectures. - Develop and improve the operational excellence, data quality, monitoring and data governance. BASIC QUALIFICATIONS - Bachelor More ❯

a huge amount of growth and career opportunities. The ideal candidate must have: Strong Senior Data Engineer with AWS experience AWS data tooling such as S3/Glue/Redshift/SageMaker (Or relevant experience in another cloud technology). Strong experience in developing and automating scalable data pipelines in a Finance related data context. Must have a with More ❯

journey of our data platform (AWS) Cloud Proficiency: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and its core data services (e.g., S3, Redshift, Lambda/Functions, Glue). Data Modelling: Deep understanding of ELT/ETL patterns, and data modelling techniques. CRM/Customer Data Focus: Experience working directly with data from More ❯

journey of our data platform (AWS) Cloud Proficiency: Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and its core data services (e.g., S3, Redshift, Lambda/Functions, Glue). Data Modelling: Deep understanding of ELT/ETL patterns, and data modelling techniques. CRM/Customer Data Focus: Experience working directly with data from More ❯

Amazon Retail Financial Intelligence Systems is seeking a seasoned and talented Senior Data Engineer to join the Fortune Platform team. Fortune is a fast growing team with a mandate to build tools to automate profit-and-loss forecasting and planning for the Physical Consumer business. We are building the next generation Business Intelligence solutions using big data technologies such … as Apache Spark, Hive/Hadoop, and distributed query engines. As a Data Engineer in Amazon, you will be working in a large, extremely complex and dynamic data environment. You should be passionate about working with big data and are able to learn new technologies rapidly and evaluate them critically. You should have excellent communication skills and be able … to delivery high quality products. About the team Profit intelligence systems measures, predicts true profit(/loss) for each item as a result of a specific shipment to an Amazon customer. Profit Intelligence is all about providing intelligent ways for Amazon to understand profitability across retail business. What are the hidden factors driving the growth or profitability across More ❯

and transformation workflows Model and maintain curated data layers to support reporting, analytics, and decision-making Ensure high availability, scalability, and performance of data warehouse systems (cloud-based, e.g., Redshift) Develop & Manage Data Products: Collaborate with business and domain experts to define and deliver high-value, reusable data products Implement best practices around versioning, SLAs, data contracts, and quality … For 3+ years of experience as a Data Engineer, with a strong focus on data warehousing and data modeling Hands-on experience with cloud-native data tech (preferably AWS: Redshift, Glue, S3, Lambda, IAM, Terraform, GitHub, CI/CD) Proficiency in SQL and Python for data processing and automation Experience working with data modeling tools and practices (e.g., dimensional More ❯

native architectures. You'll collaborate with cross-functional teams to deliver high-impact solutions that drive business value. Requirements: Experience as a Data Engineer using AWS: Glue, Lambda, S3, Redshift, Athena, EMR. Snowflake experience (Not essential) Strong Python SQL & NoSQL databases CI/CD tools : GitHub Actions or CodePipeline Infrastructure as Code (Terraform is preferable) Experience building ETL/ More ❯

engineers and support their growth. Implement best practices for data security and compliance. Collaborate with stakeholders and external partners. Skills & Experience: Strong experience with AWS data technologies (e.g., S3, Redshift, Lambda). Proficient in Python, Apache Spark, and SQL. Experience in data warehouse design and data migration projects. Cloud data platform development and deployment. Expertise across data warehouse and More ❯

Strong background in software engineering , with expertise in cloud computing and DevOps practices . Hands-on experience building, deploying, and maintaining services in AWS (e.g., EC2, Lambda, S3, RDS, Redshift, and other AWS services). Proficiency in programming languages such as Python (preferred), Java, or Go. Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation). Experience building scalable More ❯

Snowflake (data warehousing and performance tuning) Informatica (ETL/ELT development and orchestration) - nice to have Python (data processing and scripting) - required AWS (data services such as S3, Glue, Redshift, Lambda) - required Cloud data practices and platform - AWS required Basic knowledge of related disciplines such as data science, software engineering, and business analytics. Proven ability to independently resolve complex More ❯

best practices and aligned with the client's enterprise strategy. Proven experience as a Data Solution Architect, with expertise in various AWS services such as EC2, S3, Aurora, DynamoDB, Redshift, Lambda, Glue, Athena, Quicksight, and Sagemaker, among others. Proficiency in Snowflake's architecture and familiarity with its features, including Snowpipe, Streams, and Tasks for real-time data processing. Additionally More ❯

scalable test automation frameworks, with a focus on backend, API, and data systems using tools like Pytest and Postman. Expertise in Pandas, SQL, and AWS analytics services (Glue, Athena, Redshift) for data profiling, transformation, and validation within data lakes. Solid experience with AWS (S3, Lambda, EMR, ECS/EKS, CloudFormation/Terraform) and understanding of cloud-native architectures and More ❯

scalable test automation frameworks, with a focus on backend, API, and data systems using tools like Pytest and Postman. Expertise in Pandas, SQL, and AWS analytics services (Glue, Athena, Redshift) for data profiling, transformation, and validation within data lakes. Solid experience with AWS (S3, Lambda, EMR, ECS/EKS, CloudFormation/Terraform) and understanding of cloud-native architectures and More ❯

Engineers and Associates, and lead technical discussions and design sessions. Key requirements: Must-Have: Strong experience with AWS services: Glue, Lambda, S3, Athena, Step Functions, EventBridge, EMR, EKS, RDS, Redshift, DynamoDB. Strong Python development skills. Proficient with Docker , containerization, and virtualization. Hands-on experience with CI/CD , especially GitLab CI. Solid experience with Infrastructure as Code (Terraform, CloudFormation More ❯

NumPy, Pandas, SQL Alchemy) and expert-level SQL across multiple database platforms Hands-on experience with modern data stack tools including dbt, Airflow, and cloud data warehouses (Snowflake, BigQuery, Redshift) Strong understanding of data modelling, schema design, and building maintainable ELT/ETL pipelines Experience with cloud platforms (AWS, Azure, GCP) and infrastructure-as-code practices Familiarity with data More ❯

GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF etc. Excellent consulting experience and ability to design and build solutions … experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF Desirable Skills: Designing Databricks based solutions for Azure/AWS, Jenkins, Terraform More ❯

GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent). In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF etc. Excellent consulting experience and ability to design and build solutions … experience in a similar role. Ability to lead and mentor the architects. Mandatory Skills [at least 2 Hyperscalers] GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF Desirable Skills: Designing Databricks based solutions for Azure/AWS, Jenkins, Terraform More ❯